A robust optical/inertial data fusion system for motion tracking of the robot manipulator 被引量：1

A robust optical/inertial data fusion system for motion tracking of the robot manipulator

导出

摘要 We present an optical/inertial data fusion system for motion tracking of the robot manipulator, which is proved to be more robust and accurate than a normal optical tracking system(OTS). By data fusion with an inertial measurement unit(IMU), both robustness and accuracy of OTS are improved. The Kalman filter is used in data fusion. The error distribution of OTS pro-vides an important reference on the estimation of measurement noise using the Kalman filter. With a proper setup of the system and an effective method of coordinate frame synchronization, the results of experiments show a significant improvement in terms of robustness and position accuracy. We present an optical/inertial data fusion system for motion tracking of the robot manipulator, which is proved to be more robust and accurate than a normal optical tracking system（OTS）. By data fusion with an inertial measurement unit（IMU）, both robustness and accuracy of OTS are improved. The Kalman filter is used in data fusion. The error distribution of OTS pro-vides an important reference on the estimation of measurement noise using the Kalman filter. With a proper setup of the system and an effective method of coordinate frame synchronization, the results of experiments show a significant improvement in terms of robustness and position accuracy.

作者 Jie CHEN Can-jun YANG Jens HOFSCHULTE Wan-li JIANG Cha ZHANG

机构地区 State Key Laboratory of Fluid Power Transmission and Control ABB Corporate Research China

出处《Journal of Zhejiang University-Science C(Computers and Electronics)》 SCIE EI 2014年第7期574-583,共10页 浙江大学学报C辑（计算机与电子（英文版）

基金 Project supported by the National Natural Science Foundation of China(No.51221004) Sponsored Research between ABB Re-search Ltd. and Zhejiang University

关键词 Data fusion Optical tracking Inertial measurement unit Kalman filter Data fusion,Optical tracking,Inertial measurement unit,Kalman filter

分类号 TP242 [自动化与计算机技术—检测技术与自动化装置]

引文网络
相关文献

参考文献20

1Aristidou,A,Cameron,J,Lasenby,J. Real-time estimation of missing markers in human motion capture[A].2008.1343-1346.
2Bleser,G,Stricker,D. Advanced tracking through efficient image processing and visual-inertial sensor fusion[J].Comput & Graph,2009,(01):59-72.
3Caron,F,Duflos,E,Pomorski,D. GPS/IMU data fusion using multisensor Kalman filtering:introduction of contextual aspects[J].Inform Fus,2006,(02):221-230.
4Claasen,G.C,Martin,P,Picard,F. Tracking and control for handheld surgery tools[A].2011.428-431.
5Dong,Y,Zwahlen,P,Nguyen,A.M. High performance inertial navigation grade sigma-delta MEMS accelerometer[A].2010.32-36.
6Foxlin,E,Altshuler,Y,Naimark,L. Flighttracker:a novel optical/inertial tracker for cockpit enhanced vision[A].2004.212-221.
7Park,I,Lee,B,Cho,S. Laser-based kinematic calibration of robot manipulator using differential kinematics[J].IEEE/ASME Trans Mechatron,2012,(06):1059-1067.
8Ren,H,Rank,D,Merdes,M. Multisensor data fusion in an integrated tracking system for endoscopic surgery[J].IEEE Trans Inform Technol Biomed,2012,(01):106-111.
9Shirinzadeh,B,Teoh,P,Tian,Y. Laser interferometry-based guidance methodology for high precision positioning of mechanisms and robots[J].Robot Comput Integr Manuf,2010,(01):74-82.
10Soroush,A,Farahmand,F,Salarieh,H. Design and implementation of an improved real-time tracking system for navigation surgery by fusion of optical and inertial tracking methods[J].Appl Mech Mater,2012.273-279.